Mothers with depression have also been found to display less sensitivity toward their children (Murray treatment junctional tachycardia purchase finax 1 mg line, Fiori-Cowley symptoms rabies order 1 mg finax free shipping, Hooper symptoms high blood sugar buy discount finax 1 mg on-line, & Cooper lanza ultimate treatment cheap finax 1mg free shipping, 1996) and use harsher discipline with their children (Kiernan & Huerta medications covered by medi cal cheap finax 1mg with visa, 2008) treatment 6th feb buy finax 1mg on-line. Chronicity of depression also plays a crucial role in determining less optimal mother-infant interaction (Campbell, Cohn, & Meyers, 1995). Researchers administered a diagnostic interview and observed mother-infant interaction at 2, 4, and 6 months. Although the presence of depression at the 2-month follow-up was not associated with impaired mother-infant interaction, mothers who still met criteria for depression at 6 months were observed 19 to be less positive with their infants and less competent during feeding; infants were also less positive with their caregivers. These studies underscore the effects of maternal depression on both the child and caregiver. Other research has found that maternal depression affects parent-child interaction. Namely, high depressive symptoms, low maternal sensitivity, and a combination of these variables were associated with high internalizing symptoms among girls (Garai et al. While each of these studies informs the research regarding consequences of maternal depression, learning more about effects of maternal depression across different populations of families, such as high-risk families, is warranted to gain a clearer picture of the effects of depression. For years studies have been conducted to examine the mental health of mothers who are at high risk for child abuse and neglect (Milner & Chilamkurti, 1991; Milner & Crouch, 1998; Milner & Dopke, 1997). Balge and Milner (2000) assessed for differences among high- and lowrisk mothers attempting to recognize emotions in children and found that high-risk mothers made 20 more emotion recognition errors compared to low-risk mothers. Further, results found that highrisk mothers reported higher levels of depression and parenting stress than low-risk mothers. Just as it is theorized that individuals with depression exhibit negative cognitive schemas, cognitive-behavioral models propose that cognitive styles may be associated with child abuse (Milner, 1993). Collectively, this research illustrates the ability of depressive symptoms to negatively impact the family environment, thereby emphasizing the need for methods aimed at decreasing maternal depression to improve family functioning. Specifically, Scholle, Rost, and Golding (1998) utilized a sample of 303 women who had been diagnosed with depression and found that 55. One theory proposed which helps explain this relation stems from research conducted over two decades ago (Janoff-Bulman, 1989). This theory proposes that there are three basic assumptions that people have about the world: 1) the world is benevolent; 2) the world is meaningful; and 3) the self is worthy. However, when individuals are faced with traumatic events, it is thought that they must alter their assumptions about the world, adopt new ones, and/or create certain schemas in order to make sense of their "new" world (DePrince & Freyd, 2002a and DePrince & Freyd, 2002b; Martin & Kleiber, 2005). Janoff-Bulman (1992) asserts that different types of traumatic events often force people to espouse different world assumptions. Additional research is necessary to identify which protective factors are beneficial in countering these attributions since negative outcomes such as depression may surface when protective factors are absent. This "world assumptions theory" was tested in a study by Lilly, Valdez, and GrahamBermann (2011) which examined the mediating role of world assumptions on the association between trauma exposure and depression severity. The results of the study found that diminished world assumptions mediated the relation between amount of trauma exposure and depression severity. The results of this study concluded that more violence within relationships tends to lead to higher severity of depressive symptoms. Namely, various types of support are thought to affect the severity of depressive symptoms across populations. For example, religion and spirituality have been found to reduce negative mental health outcomes such as depression. This trend has been demonstrated in samples of individuals exposed to traumatic experiences such as chronic illnesses 23 (Bussing, Fischer, Ostermann, & Matthiessen, 2008; McCauley, Tarpley, Haaz, & Bartlett, 2008; Sherman, Simonton, Latif, Spohn, & Tricot, 2005) and war (Tran, Kuhn, Walser, & Drescher, 2012). Smith, McCullough, and Poll (2003) conducted a meta-analysis reporting 147 studies that have examined the relation between religiosity and depression. These researchers reported several theories as to why the two constructs tend to be inversely related such as genetic influences, developmental influences, lower substance use, increased social support, appraisal of life events, and coping abilities. Results of this meta-analysis suggest that depression is related to religiousness, and that this finding is maintained across gender, age, and ethnicity. Another protective factor discussed in literature is the concept of "family resources" which includes income, education, employment, insurance status, and self-esteem (GonzalezGuarda et al. Alternate to previously discussed research indicating that income alone is a risk factor (Allard et al. They further explain the possibility that working women may affect 24 the power dynamics in a household occupying traditional egalitarian beliefs. Additional research is warranted in different populations to assess the role of income and other family resources. These results highlight the importance of social support in the reduction of poor mental health outcomes among abused women. Thus, it is evident that the role of social support within this relation is often crucial for psychological enhancement. In addition to the injurious effects on child functioning, Fang, Brown, Florence, & Mercy (2012) found that the estimated lifetime economic burden of child maltreatment in the United States is $124 billion, with an estimated cost of $210,012 per victim of nonfatal child maltreatment and $1,272,900 per victim of fatal child maltreatment. This collection of research emphasizes the importance of understanding protective 26 factors in such a population to aid in prevention of child abuse and neglect due to its devastatingly costly effects. Current Study the current study seeks to examine the longitudinal effects of support within a sample of high-risk families for child abuse and neglect. Additionally, the impact of risk factors (child maltreatment history) on this relation will be examined as well. Secondly, research shows that depression exhibits a different presentation and course for different populations of people (Banti et al. Additionally, the proposed study will investigate the importance of support defined in three different ways, thus extending extant research. It is composed of three modules addressing home safety, child health, and parent-child interactions. Further, exclusion criteria were (a) caregivers younger than 16 years of age, (b) limited proficiency with English language, (c) active child protective services involvement at the time of the referral and (d) more than two previous referrals to child protective services. Demographic information was collected from participants and included the following information: gender, ethnicity, age, marital status, education level, size of the town in which they live, information regarding government assistance, number and ages of children in the home, whether or not they are pregnant, and current work status. Though this scale consists of subscales measuring five different constructs (Negotiation, Psychological Aggression, Physical Assault, Injury, and Sexual Coercion), the current study only utilized the Physical Assault subscale which consists of twelve items. Each item has a four-point scale ranging from 0 to 3, and items are summed to provide a single score of depression. For the current study, participants were classified into two groups-those with depression and those without depression based on a cutoff score of 19. Depression was dichotomized in order to create a group of individuals with depression and a group of individuals without depression, based on the 30 guidelines by the developers of the measure (Beck et al. Dichotomizing this variable creates groups based on a clinically relevant cut-off point (Beck and colleagues,1996), thus allowing for a straightforward interpretation of regression coefficient estimates. Each item corresponds to a 5-point likert scale ranging from 1 ("not at all adequate") to 5 ("almost always adequate"). This scale has shown evidence of validity (Roberts, Lepore, & Helgeson, 2006) and internal consistency (Ergh, Hanks, Rapport, & Coleman, 2003) across a variety of samples, including nursing home patients, cancer patients, and 31 economically-disadvantaged individuals across different cultures. Participants were characterized as having a history of child maltreatment if responded positively to any of these items. Procedure Approval from the appropriate Institutional Review Board was obtained prior to implementation of the study procedures. At each wave, participants completed a battery of measures on protective and risk factors associated with child maltreatment including the demographics questionnaire. To reimburse them for their time, participants received a $50 gift certificate to a local home needs establishment for each assessment. This assumption was found to be plausible using a simple test proposed by Park and Davis (1993). Briefly, we defined indicator variables for each missing data pattern and fit an extended model which includes the indicator variables and covariates of interest. Then, we performed the test for the missing data mechanism by testing whether or not the regression coefficients are associated with the indicator variables are zero. Of the 562 study participants, 54 had missing values at any wave for at least one risk factor and were omitted from the group-based modeling. The cross-sectional relationships between response variable (depression scores) and time independent (program assignment, ethnicity, etc. The median number of days between assessments was 287 days for wave 1 to wave 2 (n=499), 234 days for wave 2 to wave 3 (n=399) and 593 days for wave 1 to wave 3 (n=381). Group-Based Trajectory Modeling (Hypothesis Two) Group-based trajectory modeling (Nagin & Land, 1993) was used to examine the second study hypothesis. Group based trajectory modeling assumes that there are a certain number of discrete underlying groups in the study population that have varying depression prevalence, and patterns of change over time. These sub-populations are not directly observable, but are estimated (latent) and are used to help us better understand the etiological underpinnings of different depression trajectories (Nagin et al. Model selection involved an iterative estimation of (1) the number of trajectory groups and (2) the shape of each trajectory group using both statistical and non-statistical considerations. The resulting final 2-group model was assessed for goodness of fit based on standard criteria, that is, (1) the average posterior probabilities for each of the emergent subgroups, (2) odds of correct classification, and (3) comparison of actual (based on posterior probabilities) to model estimated group prevalence (Nagin, 2005). The non-statistical considerations included, reasonable sample sizes in each identified trajectory group, nonoverlapping confidence intervals and distinct average posterior probabilities across groups to help achieve a clinically useful and parsimonious model (Nagin et al. The odds of belonging to group 2 relative to the reference group (Group 1) were based on selected time-invariant characteristics. At baseline, participants consisted of 562 individuals ranging in age from 16-65 (M = 25. One hundred, forty-six (26%) individuals reported a 9th to 12th grade education, and one hundred, eighty-four (32. Cross-Sectional (Bivariate) Analyses Results of bivariate descriptive analyses are summarized in Table 2. Longitudinal Analyses Overall, depression symptoms visually declined over time as illustrated in Figure 1. Participants who reported higher frequencies of religious house of worship attendance reported lower depression symptoms over time (Figure 3). Figure 4 shows that participants with high social support (3rd and 4th quartile) scores have visually lower depression scores than those with low social support. Depression symptoms decline faster (steeper slope) among participants who reported low social support than those with high social support at baseline. Figure 5 shows that participants with high family resource (3rd and 4th quartile) scores have visually lower depression scores than those with low family resources. The decline in depression symptoms over time is most pronounced among participants who reported low family resources than those with high family resources at baseline. Regarding main effects of types of support on depression, a visual difference between the four church attendance groups (Never, Only on special occasions, About once per month, About 38 once per week, More than once per week) exists, though the effects were not statistically significant. Specifically, participants who reported never attending religious services had higher levels of depression than individuals in each of the other groups. Figure 4 illustrates the finding that participants who reported less social support at baseline also reported higher levels of depression over time compared to participants who reported more social support. Finally, participants who reported having fewer family resources at baseline had higher depression scores at wave 1, though this trend decreased at waves 2 and 3. Caregivers who had above average levels social supports and family resources had lower odds of depression over time than caregivers with below average levels of supports (adjusted odds ratio: 0. For every level increase in 39 church attendance, the odds of depression decreased by 14% over time, however, this result was not statistically significant (adjusted odds ratio: 0. Group-Based Modeling (Hypothesis Two) It was hypothesized that distinct subgroups would exist within the study sample with respect to the presentation of depression status over time; this hypothesis was supported by the data. Namely, a two-group linear trajectory model best fit participant depression status (Figure 9; Table 5). The largest percentage of the sample, 73%, exhibited low and somewhat decreasing probability of depression over time (Group 1). The rate of decrease was greater between baseline and the follow-up assessment than between the first and second assessment. The percentages of correct group membership are high, with 91% for group 1 and 84% for group 2. Since the misclassification in both groups is relatively small, the estimated population group proportions (73% for group 1 and 27% for group 2) are close to the sample membership proportions (76% for group 1 and 23% for group 2). The risk factor parameters, standard errors, test statistics, and significance (p values) for these tests are presented in Table 6. Program assignment, pregnancy status and age were not significant predictors of group membership (p >. In comparison to the low depression group, the protective effects of above average levels of social support and family 41 resources were accentuated in this group. In both the low and persistent depression groups, the odds of depression over time were not impacted by different levels of church attendance among participants (p >. These variables are as follows: program effects (SafeCare versus Services as Usual), pregnancy, and psychotropic medication. These variables were controlled in analyses conducted for hypotheses one through three. The odds of depression among participants who reported taking psychotropic medications were 3. Among those in the low depression group, there was a significant program effect on the odds of depression over time (= -0. Consistent with results observed in the low depression group, the odds of depression among psychotropic medication users were 3. The potential for unobserved heterogeneity within this study sample was examined using group based models. Consistent with our hypothesis, there were identifiable distinct depression trajectory groups in the study sample. One group of participants had persistent depression throughout study follow-up, while another group displayed low levels of depression. Therefore, on average, participants reported 44 depression levels below the cut-off score of 19.
Moreover 88 treatment essence buy generic finax 1mg, androidbased applications can be run on virtually any personal computers through the android emulator; and this capability promotes the growth of android market globally treatment 5th finger fracture discount finax 1mg, leaving behind many rivals in its trail treatment for hemorrhoids purchase 1 mg finax mastercard. Mobile learning Application Learning Environment [3] Mobile learning is developed by using multi platforms medicine zetia buy cheap finax 1 mg on line, languages medicine vs dentistry buy 1mg finax with amex, and technologies medicine woman cast discount finax 1mg mastercard. In this regard, android technology can help realize a mobile learning environment based on the network architecture shown with students gaining fast access to learning contents and materials of their studies by using their mobile phones. This approach of learning is highly receptive to students as they are more likely to seek and use learning contents via mobile services rather than to find proprietary courseware that is not easily accessed. Teaching and learning has become more manageable and diverse as students can perform many learning activities freely and easily, for instance, they can download lectures notes almost instantaneously for lectures that they had missed. For example, students can download and practice short tests or quizzes on their mobile phones where prompt feedback is instantly displayed to improve comprehension this type of learning occurring in short bursts is appealing to young generation [7]. In addition, students can download notes from Google doc website using android platform. Currently, the technology enables students to share and edit documents online collaboratively; thus, the notion of collective intelligence has transformed from an abstract concept into tangible realization in the educational realm. Figure 3 shown below illustrates the interface for students to download documents over the related website. Google Doc Third, there exists a repository of knowledge for sharing information among practitioners of mobile learning that contributes to the expansion of M-learning in campuses. This creates a community of practice that continually enhances the technical capabilities of M-learning systems irrespective of their background. In spite of the many benefits accorded by M-learning, there are still some issues that need to be addressed by many concerned. For example, it is not that easy to measure the actual level of meaningful learning that takes place using this type of learning at best, and such a mode of learning can be easily abused at worst. Assimilating this technology into normal classroom activities requires not only structural changes but new thinking regarding learning of this nature is urgently required [8]. This problem is further compounded as individuals involved in M-learning come with different knowledge, skills, and expertise; and understandably, their Mobile learning is a form of digital learning which can be applied for teaching and learning purposes where some educational experts view it as a subset of e-learning but with a subtle difference-contents are delivered onto mobile devices rather than the ubiquitous desktop personal computers. Teaching and learning by using android platform can be easily implemented without heavy computing investment. First, android operating system to run the mobile devices is conveniently and freely available, thus making installation a simple, neat process. Clearly, the respondents that had used the mobile learning system were more receptive to using the system where they regarded the system to be easy to use and also to be interesting. The survey was conducted involving a total of 56 students were voluntarily participated in this study. For the learning materials, the two groups of students had to download notes from two different platforms. The first group downloaded learning materials from the e-learning system of the university, whilst the second group of students downloaded similar materials from Google Doc by using their mobile phones. Likewise, the same perceptions of the respondents were elicited for the e-Learning environment system. Respondents were asked for their opinions on the items of the questionnaire based on Likert-type scales as follows: 1 for strong disagreement, 2 for disagreement, 3 for being neutral, 4 for agreement, and 5 for strong agreement. Findings and Discussion Table I as shown below summarizes the descriptive statistics for the respondents demographic based on frequency counts. This finding is not surprising as androidbased mobile phones are quite affordable to own, and in terms of performance, they are very stable and could perform all the necessary functions with greater ease. These two factors seem to be a driving force to spur greater growth of mobile learning in the future. Evidently, this feature of greater capability for downloading is better accorded by mobile learning platform compared to e-learning platform. Apparently, there are several reasons why mobile learning is greatly favored for this feature of a digital learning system. First, a learning system that guarantees uninterrupted access to learning materials can ensure smooth flow of learning process where students can download any documents at any time, no matter where they are. On the other hand, the availability of lecture materials by many e-learning systems is sometimes compromised by technical problems with most cases resulting in breakdowns, which hinder constant access for online documents. These students had ample time to download lecture notes from the Google Doc website without interruptions, and they could take quizzes and short tests at leisure, which further enriches their learning experience. This is not unexpected as there is a vast repository of learning tools, widgets, and applications that could be accessed freely or bought at minimal cost from the android market. Once downloaded, all these digital materials can be utilized instantly and repetitively. In sum, this research suggests that mobile learning can be quite easily implemented as clearly demonstrated by the respondents involved in this study. Mobile learning can be cost-effectively implemented as android operating system used to run the mobile phones is freely available. Moreover, newer, better versions of this operating system are constantly update, giving better performance in terms of processing and intuitive interface design. Mobile learning systems powered by android technology can make learning more fun, interactive and intuitive. This mobile learning system can be used by educational practitioners, such as instructors and teachers, to prepare the study notes in any standard digital formats and then upload them onto the Google Doc website, where they can be accessed and shared. However, as for today, there are many emerging information and communication technologies entering the educational realm that forces practitioners to rethink how this novelty can be judiciously applied to improve the overall learning process. Many educational benefits of the novelty can be easily identified; however, realizing these is not a straightforward process as there is a web of interrelated factors that needs delicate unweaving to ensure effective and efficient implementations in educational institutions. Smart phones, a powerful tool in Chemistry classroom, Journal of Chemical Education, 88, 683-686. He specializes in Software Engineering and E-Learning Technologies (Email: apiltzs@gmail. He specializes in Virtual Reality in Education and Engineering (Email: khairul@fskik. Expectedly, the introduction of any new, novel technology would have profound impact, affecting both students and educators. Students will be overwhelmed with the technological gizmo that is normally designed for routine chores, not for educational purposes. Thus, proper working ethics and code of practices are entailed to ensure optimal use of mobile devices for mobile learning. Likewise, educators must keep abreast with latest technologies to make efficient use of them. Therefore, future research should focus some of these issues to help realize digital learning environments that complement the conventional learning approach. The protocol will allow two parties to sign the same contract and then exchange their digital signatures. The protocol consists of only three messages that are exchanged between the two parties. That is, the parties gradually exchange their signatures in part until both signatures are complete. If one party fails to send an additional part of the signature, the other party works to search for that remaining part. The gradual exchange protocols are based on the assumption that the two parties have the same computational power to ensure fairness. The gradual exchange protocols require a large number of rounds to complete the exchange of signatures. If one party fails to submit their signature, the third party will be brought in to resolve any dispute. Also, the turnaround time is eliminated since the parties exchange their signatures directly. This category overcomes the farness problem by using verifiable and recoverable encrypted signatures. Lets say that two contracting parties, Alice and Bob, want to exchange their signatures on a contract. Traditionally, paper-based contracts are signed by the transacting parties who need to be present at the same venue and at the same time. Each party signs a copy of the contract for every contracting party so that every party has a copy of the signed contract. If the parties, however, are not able to meet to sign the paper-based contract, then signing an electronic contract is an alternative. The problem with signing electronic contracts, however, is exchanging the signatures of the parties, especially where there is a lack of trust between parties. One party may send the other party their signature on the contract but may not receive the signature of the other party in return. To solve the problems of exchanging digital signatures, contract signing protocols are used [3, 4, 5, 9, 10]. In the normal execution of the protocol, the two parties will exchange their signatures directly. The comparison of the proposed protocol with related protocols is presented in section V. Bob will then verify the encrypted signature and if it is correctly verified, send his signature to Alice. The protocol is based on the verifiable and recoverable encryption of signatures on a contract. Alice will send her partially encrypted signature to Bob who will be able to verify it. If the encrypted signature is correctly verified then Bob will send Alice his signature. If Alice and Bob want to exchange their signatures on a contract then the protocol will work as follows. Alice will then send Bob: (1) the encrypted signature, (2) evidence stating that Alice has correctly encrypted her signature on the contract. If the evidence is valid then Bob will send his signature on the contract to Alice. In this paper, we propose a new approach that uses verifiable and recoverable encryption of signatures that will allow the party who receives the encrypted signature to verify it. The proposed protocol does not use the interactive zero-knowledge proofs for verifying the encrypted signature as in [4 & 5]. Rather, the contract certificate that is introduced in this paper will allow the party who receives the encrypted signature to verify it. The digital signature of party x on M is computed by encrypting the hash value of M using the private key skx(dx, nx). The contents of C-Cert are: o heSig: the hash value of the signature of Pa on the contract encrypted with pkat i. Assumptions the following represents the assumptions used in the proposed protocol: Channels between Pa, Pb and Pt are resilient i. Pt is trusted by all parties and will not collude with any other party Parties Pa and Pb will agree on the contract before the protocol starts 68 P a g e The shared public key is denoted as pkat = (eat, nat) and its corresponding private key is denoted as skat = (dat, nat). Pt will certify the shared public key and issue the shared public key certificate C. If all verifications are correct then Pb will sign the contract using their private key skb then will send the signed contract "Sig. That is, Pa will decrypt the signature to get the hash value of the contract then compare it with "hC" that is included in C-Cert. If Pa did not send E-M3 or sent incorrect E-M3 then Pb can contact Pt using the dispute resolution protocol to resolve the dispute. Exchange Protocol the exchange protocol represents the normal execution of the protocol. Dispute Resolution Protocol If Pb did not receive the step E-M3 or received an incorrect E-M3, Pb can contact Pt to resolve the dispute. If the certificates are correctly verified then Pt will verify the correctness of the encrypted signature of Pa on the contract i. To verify the encrypted signature, Pt will either (i) compute the hash value of enc. Exchange Protocol Step [E-M1]: Pa encrypts the signed contract with the shared public key pkat. Step [E-M2]: once Pb receives E-M1 then they will do the following verifications: 1. If the certificates are correctly verified then Pb will compute the hash value of the contract and then compare it with "hC" that is included in C-Cert. Pb will also need to verify the correctness of the encrypted signature of Pa on the contract i. If they match it means that Pa encrypted the correct signature, or (ii) Pt has the private key "skat" corresponding to the shared public key so it can decrypt the encrypted signature i. If both Pa and Pb act honestly then fairness will be ensured in the exchange protocol and there is no need to contact Pt at all. Therefore, the above analysis of the four cases shows that the fairness is ensured either in the exchange protocol or in the dispute resolution protocol. It is worth mentioning that Pt does not need to receive any message from Pa in order to resolve any dispute raised by Pb. If the request is valid then Pt will send the resolution electronically to both Pb and Pa. That is, every time Pa and Pb need to exchange their signatures on a contract then a new certificate will be used. For the comparison, we analyze the number of messages and the number of modular exponentiations in both the exchange protocol and dispute resolution protocol. The exponentiation is the most expensive cryptographic operation in the finite field [5]. Regarding the modular exponentiations in the exchange protocol, the proposed protocol has the lowest number of modular exponentiations, with only six.
Discount 1mg finax otc. Strep can Cause OCD Symptoms: Learn About PANDAS/PANS with Beth Maloney.
Syndromes
Your body has a hard time getting rid of uric acid
Fluids by IV
Blood clots in the legs that may travel to the lungs
Valdes AM, McWilliams D, Arden NK, et al. Involvement of different risk factors in clinically severe large joint osteoarthritis according to the presence of hand interphalangeal nodes. Arthritis Rheum 2010; 62(9):2688-95.
Abramov A, Schorr S, Wolman M. Generalized xanthomatosis with calcified adrenals. Am J Dis Child 1956;91:282.
Lindberg K, Amin R, Moe OW, et al. The kidney is the principal organ mediating klotho effects. J Am Soc Nephrol. 2014;25:2169.
